Infrastructure on ThecoreGrid covers the design, operation, and evolution of the foundational systems that power modern software at scale.
We explore compute, networking, and storage layers, along with virtualization, containers, and cloud platforms in highload environments. The focus is on production-grade engineering: reliability, fault tolerance, capacity planning, cost efficiency, and secure system design. Topics include Infrastructure as Code, automation, provisioning, multi-region setups, traffic routing, and failure recovery. We analyze real-world trade-offs and operational challenges, supported by BigTech practices, incident post-mortems, and lessons from large-scale infrastructure failures. You’ll find deep dives into observability, performance tuning, and platform reliability under dynamic workloads. Instead of basic setup guides, the Infrastructure tag delivers practical insights for platform engineers, DevOps teams, SREs, and architects responsible for building and maintaining robust, scalable, and efficient infrastructure systems.
Platform Program split became a key step for Uber when the growth of the team began to hinder development. This decision changed both the architecture and the organization simultaneously. The problem manifested not at the code level, but at the level of team interaction. When Uber’s engineering organization grew to about 100 people, the division … Read more
P2P model distribution in Kubernetes with Dragonfly: how to reduce traffic to the origin and accelerate the delivery of large models from Hugging Face and ModelScope.
Migration from Ingress NGINX is becoming mandatory: EOL and vulnerabilities make the transition to Kubernetes Gateway API a matter of resilience and security. The problem does not manifest immediately — until control over incoming traffic becomes a point of systemic risk. Ingress NGINX has long been the de facto standard for Kubernetes, but its lifecycle … Read more
Symbolic execution simplifies the analysis of BPF malware and eliminates a bottleneck in reverse engineering. This approach allows for the automatic reconstruction of “magic” packets to trigger backdoors. The problem does not manifest immediately — until the analysis of BPF malware encounters the complexity of the filters themselves. The classic Berkeley Packet Filter operates as … Read more
Tagged storage pattern for multi-tenant configurations on AWS: how to eliminate cache staleness and scale the metadata service without sacrificing performance.
LLM Infrastructure, GPU Inference, Agentic Systems, Distributed Systems, High Performance Computing, HPC, Cloud Native, Data Infrastructure
Agent Reliability Score explains how the platform affects the reliability of AI agents and why context control is critical for production systems.
How DWDP optimizes LLM inference by eliminating inter-GPU synchronization and increasing throughput in multi-GPU systems.
Cloudflare Organizations simplifies RBAC in multi-account environments: centralized control, faster access reviews, and reduced management complexity.
Topology-preserving compression without sacrificing speed: how EXaCTz achieves GB/s throughput while preserving the contour tree and extremum graph.
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